| d02pdc | Ordinary differential equations solver, initial value problems, one time step using Runge–Kutta methods |
| g05hac | ARMA time series of n terms |
| g05hkc | Univariate time series, generate n terms of either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2 |
| g05hlc | Univariate time series, generate n terms of a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
| g05hmc | Univariate time series, generate n terms of an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
| g05pac | Generates a realisation of a time series from an ARMA model |
| g05pcc | Generates a realisation of a multivariate time series from a VARMA model |
| g13aac | Univariate time series, seasonal and non-seasonal differencing |
| g13asc | Univariate time series, diagnostic checking of residuals, following g13bec |
| g13bac | Multivariate time series, filtering (pre-whitening) by an ARIMA model |
| g13bbc | Multivariate time series, filtering by a transfer function model |
| g13bcc | Multivariate time series, cross-correlations |
| g13bdc | Multivariate time series, preliminary estimation of transfer function model |
| g13bec | Estimation for time series models |
| g13cac | Univariate time series, smoothed sample spectrum using rectangular, Bartlett, Tukey or Parzen lag window |
| g13cbc | Univariate time series, smoothed sample spectrum using spectral smoothing by the trapezium frequency (Daniell) window |
| g13ccc | Multivariate time series, smoothed sample cross spectrum using rectangular, Bartlett, Tukey or Parzen lag window |
| g13cdc | Multivariate time series, smoothed sample cross spectrum using spectral smoothing by the trapezium frequency (Daniell) window |
| g13cec | Multivariate time series, cross amplitude spectrum, squared coherency, bounds, univariate and bivariate (cross) spectra |
| g13cfc | Multivariate time series, gain, phase, bounds, univariate and bivariate (cross) spectra |
| g13cgc | Multivariate time series, noise spectrum, bounds, impulse response function and its standard error |
| g13dbc | Multivariate time series, multiple squared partial autocorrelations |
| g13dlc | Multivariate time series, differences and/or transforms |
| g13dmc | Multivariate time series, sample cross-correlation or cross-covariance matrices |
| g13dnc | Multivariate time series, sample partial lag correlation matrices, χ2 statistics and significance levels |
| g13dpc | Multivariate time series, partial autoregression matrices |
| g13eac | One iteration step of the time-varying Kalman filter recursion using the square root covariance implementation |
| g13ebc | One iteration step of the time-invariant Kalman filter recursion using the square root covariance implementation with (A,C) in lower observer Hessenberg form |
| g13ecc | One iteration step of the time-varying Kalman filter recursion using the square root information implementation |
| g13edc | One iteration step of the time-invariant Kalman filter recursion using the square root information implementation with (A-1, A-1 B) in upper controller Hessenberg form |
| g13fac | Univariate time series, parameter estimation for either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2 |
| g13fbc | Univariate time series, forecast function for either a symmetric GARCH process or a GARCH process with asymmetry of the form (εt-1 + γ)2 |
| g13fcc | Univariate time series, parameter estimation for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
| g13fdc | Univariate time series, forecast function for a GARCH process with asymmetry of the form (|εt-1| + γ εt-1)2 |
| g13fec | Univariate time series, parameter estimation for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |
| g13ffc | Univariate time series, forecast function for an asymmetric Glosten, Jagannathan and Runkle (GJR) GARCH process |